基于核密度函数的多尺度北京市休闲农业空间分布分析
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摘要
核密度函数估计法是常用的分析城市点要素空间分布模式的方法。使用核密度函数估计法的关键是最佳带宽的确定。目前,大多数研究使用单纯基于数学的方法或目视判读法确定核密度函数的最适带宽,但是针对同一地理实体在不同分析尺度上所对应的核密度函数适用带宽确定方法问题研究相对不足。该文考虑了北京市休闲农业本身所具有的尺度特征,基于北京市休闲农业POI数据,使用核密度函数评估方法,识别并分析其多尺度空间分布模式,并使用文献求证法进行了验证。使用Moran’I、HH个数和Comprehensive I指数曲线相结合的方法确定了适合分析北京市休闲农业区域尺度和局部尺度空间分布模式的核密度函数所对应的带宽,分别为9 km和3 km。进而分析了北京市休闲农业多尺度空间分布模式。北京市休闲农业空间分布模式在区域尺度上形成了2个圈层及多个聚集中心的结构。距离城市中心约30～50 km的圈层为1日游圈层。距离城市中心约50～90 km的圈层为2日游或多日游圈层。1个主中心位于昌平区东部、怀柔区东南部、密云区西南部的山前平原地区。2个副中心分别位于密云区东北部和房山区西南部;在局部尺度上形成了3个等级的26个小的聚集中心,第一等级2个,第二等级3个,第三等级21个,主要位于中北部的山前平原地区,东南部城乡交错带的平原地区及西部山区分布相对较少,中心城区分布最少。该研究可为北京市休闲农业空间规划提供重要参考依据。
With the improvement of urban economic development, leisure agriculture becomes one of the important forms of the integration development of rural and urban region. The distributions pattern of the leisure agriculture could be studied in multi-scale(from local scale to regional scale). Based on regional economic statistical data, recent researches exploring the spatial distribution pattern of leisure agriculture were difficult to accurately describe because the analyzing scale was too large. Recently, point of interest(POI) data has been widely applied to analyze features of the urban to show the spatial distribution patterns with advantages of large data volume, high position accuracy and the clear classification of the leisure agriculture format. While the researches on the distribution pattern of the leisure agriculture based on POI were rather inadequate. The key to apply kernel density estimation(KDE) for spatial distribution pattern of urban point element was exploring the suitable bandwidth. So far, most of researches on bandwidth determination of KDE were based on mathematical or visual interpretation methods. Considering the scale features of spatial distribution pattern, basing on POI data, applying the method of spatial autocorrelation to determine different bandwidths of KDE which suited to analyze the regional-scale and local-scale spatial distribution patterns, this paper has recognized and analyzed the multi-scale features of spatial distribution patterns on Beijing leisure agriculture. The spatial autocorrelation method contained 2 indices, Moran'I and Local Moran'I. With increasing of KDE bandwidth, the value of the normalized Moran'I gradually increased from 0 to 1 and the value of the normalized number of HH(a statistically significant cluster of high values) region from the result of local Moran'I decreased from 1 to 0. At this time, the result of KDE could express the regional scale distribution pattern of leisure agriculture and the detail features were covered. On the contrary, the result of KDE could express the small scale pattern of Beijing leisure agriculture and the detail features were obvious. Considering the variable characteristics of Moran'I, the number of HH and comprehensive I curves, this paper determined different bandwidths of KDE which suited to analyze the regional-scale and local-scale spatial distribution pattern of the leisure agriculture were 9 km and 3 km. Using the method of natural breaks, the results of KDE with 9 km or 3 km bandwidths were divided into three levels, high value, middle value and low value respectively. Then spatial distribution patterns with different scales were identified. Under the regional-scale, the spatial distribution pattern showed two rings and multi-centers. The interior ring away from the city center from 30 km to 50 km was one day tour zone. The exterior ring away from the city center from 50 km to 90 km was two days and up tour zone. It was found that a primary distribution center was lied in the sub-montane area in the east of Changping County, the southeast of Huairou County, the southwest of Miyun County. Two sub-centers were lied in the northeast of Miyun County and the southwest of Fangshan County. Under the local-scale, the spatial distribution pattern showed 26 centers divided into 3 classes by area size. Most centers lied in the sub-montane area in the north to the middle part of Beijing. Fewer lied in the rural-urban fringe area in the southeast and hills in the west of Beijing. The least lied in the central city area. Finally the literature analysis method was applied to certificate the multi-scale features of the spatial distribution pattern on Beijing leisure agriculture. The method proposed in this paper is effective to express the different scales of spatial distribution pattern on Beijing leisure agriculture.
With the improvement of urban economic development, leisure agriculture becomes one of the important forms of the integration development of rural and urban region. The distributions pattern of the leisure agriculture could be studied in multi-scale(from local scale to regional scale). Based on regional economic statistical data, recent researches exploring the spatial distribution pattern of leisure agriculture were difficult to accurately describe because the analyzing scale was too large. Recently, point of interest(POI) data has been widely applied to analyze features of the urban to show the spatial distribution patterns with advantages of large data volume, high position accuracy and the clear classification of the leisure agriculture format. While the researches on the distribution pattern of the leisure agriculture based on POI were rather inadequate. The key to apply kernel density estimation(KDE) for spatial distribution pattern of urban point element was exploring the suitable bandwidth. So far, most of researches on bandwidth determination of KDE were based on mathematical or visual interpretation methods. Considering the scale features of spatial distribution pattern, basing on POI data, applying the method of spatial autocorrelation to determine different bandwidths of KDE which suited to analyze the regional-scale and local-scale spatial distribution patterns, this paper has recognized and analyzed the multi-scale features of spatial distribution patterns on Beijing leisure agriculture. The spatial autocorrelation method contained 2 indices, Moran'I and Local Moran'I. With increasing of KDE bandwidth, the value of the normalized Moran'I gradually increased from 0 to 1 and the value of the normalized number of HH(a statistically significant cluster of high values) region from the result of local Moran'I decreased from 1 to 0. At this time, the result of KDE could express the regional scale distribution pattern of leisure agriculture and the detail features were covered. On the contrary, the result of KDE could express the small scale pattern of Beijing leisure agriculture and the detail features were obvious. Considering the variable characteristics of Moran'I, the number of HH and comprehensive I curves, this paper determined different bandwidths of KDE which suited to analyze the regional-scale and local-scale spatial distribution pattern of the leisure agriculture were 9 km and 3 km. Using the method of natural breaks, the results of KDE with 9 km or 3 km bandwidths were divided into three levels, high value, middle value and low value respectively. Then spatial distribution patterns with different scales were identified. Under the regional-scale, the spatial distribution pattern showed two rings and multi-centers. The interior ring away from the city center from 30 km to 50 km was one day tour zone. The exterior ring away from the city center from 50 km to 90 km was two days and up tour zone. It was found that a primary distribution center was lied in the sub-montane area in the east of Changping County, the southeast of Huairou County, the southwest of Miyun County. Two sub-centers were lied in the northeast of Miyun County and the southwest of Fangshan County. Under the local-scale, the spatial distribution pattern showed 26 centers divided into 3 classes by area size. Most centers lied in the sub-montane area in the north to the middle part of Beijing. Fewer lied in the rural-urban fringe area in the southeast and hills in the west of Beijing. The least lied in the central city area. Finally the literature analysis method was applied to certificate the multi-scale features of the spatial distribution pattern on Beijing leisure agriculture. The method proposed in this paper is effective to express the different scales of spatial distribution pattern on Beijing leisure agriculture.
引文
[1]杨卫丽,李同昇.西安都市圈都市农业发展及空间格局研究[J].经济地理,2011,31(1):123-128.Yang Weili,Li Tongsheng.Urban agriculture development and the study of spatial pattern about xi'an metropolitan area[J].Economic Geography,2011,31(1):123-128.(in Chinese with English abstract)
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[4]Walford Nigel.Patterns of development in tourist accommodation enterprises on farms in England and Wales[J].Applied Geography,2001,21(4):331-345.
[5]王树进,陈宇峰.我国休闲农业发展的空间相关性及影响因素研究[J].农业经济问题,2013(9):38-45.
[6]许志晖,戴学军,庄大昌,等.南京市旅游景区景点系统空间结构分形研究[J].地理研究,2007,26(1):132-140.Xu Zhihui,Dai Xuejun,Zhuang Dachang,et al.A fractal study on spatial structure of tourist scenic spots systems:Acase study of Nanjing[J].Geographical Research,2007,26(1):132-140.(in Chinese with English abstract)
[7]陈鸥,杨艳茹.都市农业的多功能性与圈层布局[C]//海峡两岸观光休闲农业与乡村旅游发展学术研讨会,2002.
[8]Xie Zhixiao,Yan Jun.Kernel density estimation of traffic accidents in a network space[J].Computers,Environment and Urban Systems,2008,32(5):396-406.
[9]邓敏.空间聚类分析及应用[M].北京:科学出版社,2011.
[10]Elgammal A,Duraiswami R,Harwood D,et al.Background and foreground modeling using nonparametric kernel density estimation for visual surveillance[J].Proceedings of the IEEE2002,90(7):1151-1163.
[11]Alessa Lilian Naia,Kliskey Andrew Anaru,Brown Gregory.Social-ecological hotspots mapping:A spatial approach for identifying coupled social-ecological space[J].Landscape and Urban Planning,2008,85(1):27-39.
[12]Bithell J F.An application of density estimation to geographical epidemiology[J].Stat Med,1990,9(6):691-701.
[13]Wu Chao,Ye Xinyue,Ren Fu,et al.Spatial and social media data analytics of housing prices in Shenzhen,China[J].PLOSONE,2016,11(10):1-19.
[14]佘冰,朱欣焰,呙维,等.基于空间点模式分析的城市管理事件空间分布及演化--以武汉市江汉区为例[J].地理科学进展,2013,32(6):924-931.She Bing,Zhu Xinyan,Guo Wei,et al.Spatial distribution and evolution of city management events based on the spatial point pattern analysis:A case study of Jianghan district,Wuhan City[J].Progress in Geography,2013,32(6):924-931.(in Chinese with English abstract)
[15]郭福涛,胡海清,马志海.应用空间点模式方法研究大兴安岭雷击火空间分布格局[J].生态学报,2009,29(12):6741-6747.Guo Futao,Hu Haiqing,Ma Zhihai.Spatial point process for spatial distribution pattern of lightning-caused forest fires in Da Xing'an mountains[J].Acta Ecologica Sinica,2009,29(12):6741-6747.(in Chinese with English abstract)
[16]禹文豪,艾廷华,杨敏,等.利用核密度与空间自相关进行城市设施兴趣点分布热点探测[J].武汉大学学报:信息科学版,2016,41(2):221-227.Yu Wenhao,Ai Tinghua,Yang Min,et al.Detecting“Hot Spots”of facility POIs based on kernel density estimation and spatial autocorrelation technique[J].Geomatics and Information Science of Wuhan University,2016,41(2):221-227.(in Chinese with English abstract)
[17]Goodchild Michael F.Citizens as sensors:The world of volunteered geography[J].GeoJournal,2007,69(4):211-221.
[18]Goodchild Michael F.Geographic information systems and science:today and tomorrow[J].Procedia Earth and Planetary Science,2009,1(1):1037-1043.
[19]Liu Yu,Liu Xi,Gao Song,et al.Social sensing:A new approach to understanding our socioeconomic environments[J].Annals of the Association of American Geographers,2015,105(3):512-530.
[20]何忠伟,曹暕.北京休闲农业发展现状、问题及政策建议[J].北京农业,2015,(19):16-19.
[21]马世罕,戴林琳,吴必虎.北京郊区乡村旅游季节性特征及其影响因素[J].地理科学进展,2012,31(6):817-824.Ma Shihan,Dai Linlin,Wu Bihu.Analysis on the features and causes of seasonality in rural tourism:A case study of beijing suburbs[J].Progress in Geography,2012,31(6):817-824.(in Chinese with English abstract)
[22]Silverman Bernard W.Density estimation for statistics and data analysis[M].London:Chapman and Hall,1986.
[23]陈江平,张瑶,余远剑.空间自相关的可塑性面积单元问题效应[J].地理学报,2011,66(12):1597-1606.Chen Jiangping,Zhang Yao,Yu Yuanjian.Effect of MAUPin spatial autocorrelation[J].Acta Geographica Sinica,201166(12):1597-1606.(in Chinese with English abstract)
[24]陈培阳,朱喜钢.基于不同尺度的中国区域经济差异[J].地理学报,2012,67(8):1085-1097.Chen Peiyang,Zhu Xigang.Regional inequalities in China at different scales[J].Acta Geographica Sinica,2012,67(8):1085-1097.(in Chinese with English abstract)
[25]陈斐,杜道生.空间统计分析与GIS在区域经济分析中的应用[J].武汉大学学报:信息科学版,2002,27(4):391-396.Chen Fei,Du Daosheng.Regional inequalities in China at different scales application of the integration of spatial statistical analysis with GIS to the analysis of regional economy[J].Geomatics and Information Science of Wuhan University,2002,27(4):391-396.(in Chinese with English abstract)
[26]Goodchild Michael,Haining Robert,Wise Stephen.Integrating GIS and spatial data analysis:problems and possibilities[J].International Journal of Geographical Information Systems,1992,6(5):407-423.
[27]Diggle Peter.A kernel method for smoothing point process data[J].Applied statistics,1985,34(2):138-147.
[28]龚双辉.空间统计分析及在区域经济中的应用[D].武汉:华中科技大学,2007.Gong Shuanghui.Spatial Statistics Analysis and its Application in Regional Economics[D].Wuhan:Huazhong University of Science and Technology,2007.(in Chinese with English abstract)
[29]Anselin Luc,Florax Raymond J G M.New directions in spatial econometrics[M].Berlin:Heidelberg,1995.
[30]Harris Richard,Sleight Peter,Webber Richard.Geodemographics,GIS and neighbourhood targetting[J].Journal of Direct,Data and Digital Marketing Practice,2007,8(4):364-368.
[31]王劲峰,葛咏,李连发,等.地理学时空数据分析方法[J].地理学报,2014,69(9):1326-1345.Wang Jingfeng,Ge Yong,Li Lianfa,et al.Spatiotemporal data analysis in geography[J].Acta Geographica Sinica,201469(9):1326-1345.(in Chinese with English abstract)
[32]Chainey S,Reid S,Stuart N.When is a hotspot a hotspot?Aprocedure for creating statistically robust hotspot maps of crime[M].London:Taylor and Francis,2002.
[33]Yu Wenhao,Ai Tinghua,Shao Shiwei.The analysis and delimitation of central business district using network kernel density estimation[J].Journal of Transport Geography,2015,45:32-47.
[34]向雁,屈宝香,侯艳林.北京休闲农业发展现状特征及对策建议[J].中国农业资源与区划,2017,38(4):214-222.Xiang Yan,Qu Baoxiang,Hou Yanlin.Characteristics and counter measures of leisure agricuiture development in Beijing[J].Journal of China Agricultural Resources and Regional Planning,2017,38(4):214-222.(in Chinese with English abstract)
[35]钟国庆.观光休闲农业园旅游发展潜力评估:以北京市休闲果园为例[J].广东农业科学,2009(7):292-295.Zhong Guoqing.Devealopment potertial eualuation of agricalture zone for leisure and tourism:An instan a sfudy of Beijing entertainment orchand[J].Guangdong Agricultural Sciences,2009(7):292-295.(in Chinese with English abstract)
[2]郭焕成,任国柱,周聿贞.都市农业与观光农业发展研究[C]//海峡两岸观光休闲农业与乡村旅游发展学术研讨会,2002.
[3]韩春萌.基于RS的区域城市化对热岛效应的影响机制研究[D].北京:中国地质大学,2014.Han Chunmeng.The Research of the Regional Urbanization Impact on the Heat Island Based on the RS[D].Beijing:China University of Geosciences,2014.(in Chinese with English abstract)
[4]Walford Nigel.Patterns of development in tourist accommodation enterprises on farms in England and Wales[J].Applied Geography,2001,21(4):331-345.
[5]王树进,陈宇峰.我国休闲农业发展的空间相关性及影响因素研究[J].农业经济问题,2013(9):38-45.
[6]许志晖,戴学军,庄大昌,等.南京市旅游景区景点系统空间结构分形研究[J].地理研究,2007,26(1):132-140.Xu Zhihui,Dai Xuejun,Zhuang Dachang,et al.A fractal study on spatial structure of tourist scenic spots systems:Acase study of Nanjing[J].Geographical Research,2007,26(1):132-140.(in Chinese with English abstract)
[7]陈鸥,杨艳茹.都市农业的多功能性与圈层布局[C]//海峡两岸观光休闲农业与乡村旅游发展学术研讨会,2002.
[8]Xie Zhixiao,Yan Jun.Kernel density estimation of traffic accidents in a network space[J].Computers,Environment and Urban Systems,2008,32(5):396-406.
[9]邓敏.空间聚类分析及应用[M].北京:科学出版社,2011.
[10]Elgammal A,Duraiswami R,Harwood D,et al.Background and foreground modeling using nonparametric kernel density estimation for visual surveillance[J].Proceedings of the IEEE2002,90(7):1151-1163.
[11]Alessa Lilian Naia,Kliskey Andrew Anaru,Brown Gregory.Social-ecological hotspots mapping:A spatial approach for identifying coupled social-ecological space[J].Landscape and Urban Planning,2008,85(1):27-39.
[12]Bithell J F.An application of density estimation to geographical epidemiology[J].Stat Med,1990,9(6):691-701.
[13]Wu Chao,Ye Xinyue,Ren Fu,et al.Spatial and social media data analytics of housing prices in Shenzhen,China[J].PLOSONE,2016,11(10):1-19.
[14]佘冰,朱欣焰,呙维,等.基于空间点模式分析的城市管理事件空间分布及演化--以武汉市江汉区为例[J].地理科学进展,2013,32(6):924-931.She Bing,Zhu Xinyan,Guo Wei,et al.Spatial distribution and evolution of city management events based on the spatial point pattern analysis:A case study of Jianghan district,Wuhan City[J].Progress in Geography,2013,32(6):924-931.(in Chinese with English abstract)
[15]郭福涛,胡海清,马志海.应用空间点模式方法研究大兴安岭雷击火空间分布格局[J].生态学报,2009,29(12):6741-6747.Guo Futao,Hu Haiqing,Ma Zhihai.Spatial point process for spatial distribution pattern of lightning-caused forest fires in Da Xing'an mountains[J].Acta Ecologica Sinica,2009,29(12):6741-6747.(in Chinese with English abstract)
[16]禹文豪,艾廷华,杨敏,等.利用核密度与空间自相关进行城市设施兴趣点分布热点探测[J].武汉大学学报:信息科学版,2016,41(2):221-227.Yu Wenhao,Ai Tinghua,Yang Min,et al.Detecting“Hot Spots”of facility POIs based on kernel density estimation and spatial autocorrelation technique[J].Geomatics and Information Science of Wuhan University,2016,41(2):221-227.(in Chinese with English abstract)
[17]Goodchild Michael F.Citizens as sensors:The world of volunteered geography[J].GeoJournal,2007,69(4):211-221.
[18]Goodchild Michael F.Geographic information systems and science:today and tomorrow[J].Procedia Earth and Planetary Science,2009,1(1):1037-1043.
[19]Liu Yu,Liu Xi,Gao Song,et al.Social sensing:A new approach to understanding our socioeconomic environments[J].Annals of the Association of American Geographers,2015,105(3):512-530.
[20]何忠伟,曹暕.北京休闲农业发展现状、问题及政策建议[J].北京农业,2015,(19):16-19.
[21]马世罕,戴林琳,吴必虎.北京郊区乡村旅游季节性特征及其影响因素[J].地理科学进展,2012,31(6):817-824.Ma Shihan,Dai Linlin,Wu Bihu.Analysis on the features and causes of seasonality in rural tourism:A case study of beijing suburbs[J].Progress in Geography,2012,31(6):817-824.(in Chinese with English abstract)
[22]Silverman Bernard W.Density estimation for statistics and data analysis[M].London:Chapman and Hall,1986.
[23]陈江平,张瑶,余远剑.空间自相关的可塑性面积单元问题效应[J].地理学报,2011,66(12):1597-1606.Chen Jiangping,Zhang Yao,Yu Yuanjian.Effect of MAUPin spatial autocorrelation[J].Acta Geographica Sinica,201166(12):1597-1606.(in Chinese with English abstract)
[24]陈培阳,朱喜钢.基于不同尺度的中国区域经济差异[J].地理学报,2012,67(8):1085-1097.Chen Peiyang,Zhu Xigang.Regional inequalities in China at different scales[J].Acta Geographica Sinica,2012,67(8):1085-1097.(in Chinese with English abstract)
[25]陈斐,杜道生.空间统计分析与GIS在区域经济分析中的应用[J].武汉大学学报:信息科学版,2002,27(4):391-396.Chen Fei,Du Daosheng.Regional inequalities in China at different scales application of the integration of spatial statistical analysis with GIS to the analysis of regional economy[J].Geomatics and Information Science of Wuhan University,2002,27(4):391-396.(in Chinese with English abstract)
[26]Goodchild Michael,Haining Robert,Wise Stephen.Integrating GIS and spatial data analysis:problems and possibilities[J].International Journal of Geographical Information Systems,1992,6(5):407-423.
[27]Diggle Peter.A kernel method for smoothing point process data[J].Applied statistics,1985,34(2):138-147.
[28]龚双辉.空间统计分析及在区域经济中的应用[D].武汉:华中科技大学,2007.Gong Shuanghui.Spatial Statistics Analysis and its Application in Regional Economics[D].Wuhan:Huazhong University of Science and Technology,2007.(in Chinese with English abstract)
[29]Anselin Luc,Florax Raymond J G M.New directions in spatial econometrics[M].Berlin:Heidelberg,1995.
[30]Harris Richard,Sleight Peter,Webber Richard.Geodemographics,GIS and neighbourhood targetting[J].Journal of Direct,Data and Digital Marketing Practice,2007,8(4):364-368.
[31]王劲峰,葛咏,李连发,等.地理学时空数据分析方法[J].地理学报,2014,69(9):1326-1345.Wang Jingfeng,Ge Yong,Li Lianfa,et al.Spatiotemporal data analysis in geography[J].Acta Geographica Sinica,201469(9):1326-1345.(in Chinese with English abstract)
[32]Chainey S,Reid S,Stuart N.When is a hotspot a hotspot?Aprocedure for creating statistically robust hotspot maps of crime[M].London:Taylor and Francis,2002.
[33]Yu Wenhao,Ai Tinghua,Shao Shiwei.The analysis and delimitation of central business district using network kernel density estimation[J].Journal of Transport Geography,2015,45:32-47.
[34]向雁,屈宝香,侯艳林.北京休闲农业发展现状特征及对策建议[J].中国农业资源与区划,2017,38(4):214-222.Xiang Yan,Qu Baoxiang,Hou Yanlin.Characteristics and counter measures of leisure agricuiture development in Beijing[J].Journal of China Agricultural Resources and Regional Planning,2017,38(4):214-222.(in Chinese with English abstract)
[35]钟国庆.观光休闲农业园旅游发展潜力评估:以北京市休闲果园为例[J].广东农业科学,2009(7):292-295.Zhong Guoqing.Devealopment potertial eualuation of agricalture zone for leisure and tourism:An instan a sfudy of Beijing entertainment orchand[J].Guangdong Agricultural Sciences,2009(7):292-295.(in Chinese with English abstract)
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